> set.seed(42)
> area <- rnbinom(10,mu=500,size=0.5)
> riqueza <- rpois(10,lambda=(area^0.38))
> area <- c(303, 379, 961, 295, 332, 47,  122, 11, 53, 2749)
> riqueza <- c(3, 10, 20, 7, 8, 4, 8, 3, 5, 23)
> area
 [1]  303  379  961  295  332   47  122   11   53 2749
> riqueza
 [1]  3 10 20  7  8  4  8  3  5 23
> summary(area)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  11.00   70.25  299.00  525.20  367.20 2749.00 
> source("regressao.r")
> ls()
[1] "area"     "modelo1"  "modelo2"  "previsto" "riqueza"  "varea"   
> source( "regressao.r" , echo=TRUE , print.eval=TRUE )

> ##Gerando dados
> set.seed(42)

> area <- rnbinom(10,mu=500,size=0.5)

> riqueza <- rpois(10,lambda=(area^0.38))

> ##Tutorial
> area <- c(300, 350, 961, 295, 332, 47,  122, 11, 53, 2749)

> riqueza <- c(1, 7, 20, 7, 8, 4, 8, 3, 5, 23)

> area
 [1]  300  350  961  295  332   47  122   11   53 2749

> riqueza
 [1]  1  7 20  7  8  4  8  3  5 23

> summary(area)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
  11.00   70.25  297.50  522.00  345.50 2749.00 

> summary(riqueza)
   Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
   1.00    4.25    7.00    8.60    8.00   23.00 

> mean(x=area)
[1] 522

> varea <- var(area)

> varea
[1] 687272.7

> sqrt(varea)
[1] 829.0191

> sd(x=area)
[1] 829.0191

> mean(riqueza)
[1] 8.6

> var(riqueza)
[1] 51.82222

> sd(riqueza)
[1] 7.198765

> plot(x=area, y=riqueza, xlab="Area (ha)", ylab="N˙mero de EspÈcies")

> modelo1 <- lm(riqueza~area)

> summary(modelo1)

Call:
lm(formula = riqueza ~ area)

Residuals:
    Min      1Q  Median      3Q     Max 
-5.9315 -1.5771 -0.1912  0.6475  8.1006 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)   
(Intercept) 4.676806   1.451534   3.222  0.01220 * 
area        0.007516   0.001538   4.888  0.00121 **
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 3.824 on 8 degrees of freedom
Multiple R-squared:  0.7491,	Adjusted R-squared:  0.7178 
F-statistic: 23.89 on 1 and 8 DF,  p-value: 0.001213


> previsto <- fitted(modelo1)

> riqueza - previsto
          1           2           3           4           5           6 
-5.93151520 -0.30730006  8.10060888  0.10606329  0.82798249 -1.03004378 
          7           8           9          10 
 2.40627892 -1.75947867 -0.07513796 -2.33745791 

> residuals(modelo1)
          1           2           3           4           5           6 
-5.93151520 -0.30730006  8.10060888  0.10606329  0.82798249 -1.03004378 
          7           8           9          10 
 2.40627892 -1.75947867 -0.07513796 -2.33745791 

> par(mfrow=c(2,2))

> plot(modelo1)

> par(mfrow=c(1,1))

> plot(x=area, y=riqueza, xlab="Area (ha)", ylab="N˙mero de EspÈcies")

> abline(modelo1)

> plot(x=area, y=riqueza, xlab="Log Area (ha)", ylab="Log N˙mero de EspÈcies", log="xy")

> modelo2 <- lm(log(riqueza,base=10)~log(area,base=10))

> par(mfrow=c(2,2))

> plot(modelo2)

> par(mfrow=c(1,1))

> plot(area, riqueza, xlab="Log Area (ha)", ylab="Log N˙mero de EspÈcies", log="xy")

> abline(modelo2)

> # O que este comando faz?
> ## Fim!
> 